Subduction or Crustal Faulting? Evaluating Ground-Motion Models to Characterize Haida Gwaii in the Canadian Seismic Hazard Model
Bibliographic record
Abstract
ABSTRACT The tectonic classification of the Haida Gwaii thrust fault (HGT) as either a subduction interface or a crustal fault is important for seismic hazard assessment in northwest British Columbia. To inform future versions of the Canadian Seismic Hazard Model (CanadaSHM), we reviewed evidence from the literature for subduction beneath Haida Gwaii, and found that various independent geophysical datasets suggest localized incipient underthrusting along an ∼180 km segment, roughly corresponding to the 2012 rupture plane. We evaluate the performance of newly developed ground-motion prediction equations (GMPEs) for Haida Gwaii by analyzing instrumental ground motion and shaking intensity data from the 2012 Haida Gwaii earthquake, considering two magnitudes for the event (Mw 7.8 from teleseismic data and Mw 7.4 from a regional seismicity catalog). We also assess GMPE performance for another reverse-faulting earthquake that could plausibly have occurred on the HGT. Our results show that the GMPEs predict horizontal ground motions reasonably well, especially for the 2012 mainshock. On average, GMPEs overestimate shaking by a factor of 1.1 (Mw 7.4) or 1.6 (Mw 7.8), improving on earlier estimates of overprediction by a factor of two or more. Although residuals for roughly half the data overlap with the zero-residual line within uncertainty, residuals for all GMPEs tested overlap within the aleatory uncertainty of active crustal GMPEs. Therefore, ground motions are not diagnostic in terms of a crustal faulting or subduction interface designation for the HGT. We recommend that the HGT remain classified as a subduction interface in future versions of CanadaSHM, consistent with previous hazard assessments and recent studies that advocate for incipient subduction, while noting that reclassifying the HGT as an active crustal fault would have minimal impact on ground-motion simulations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".